How Credible Are Earthquake Predictions Based on TEC Variations?

Abstract

The possible relation between pre‐earthquake processes and ionospheric fluctuations is widely investigated and debated. Here, we conduct a numerical experiment to examine two studies that reported preseismic anomalies in the ionospheric total electron content (TEC) and argue for the significance of their respective analyses based on statistical evaluations. The first study is that by Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01), who statistically investigated the relationship between 62 M ≥ 6 earthquakes occurred in China over an 18‐year period and the TEC, which was deduced from the Global Ionospheric Map. According to this study, the TEC showed anomalies with specific polarities at certain days and times that preceded the earthquakes. Earthquake alarms they defined based on these anomalies showed a good performance. We conduct this same analysis using random synthetic earthquakes and obtain results that closely match those by Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01), thus indicating that the good performance of the Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01) alarm is an artifact. The second study is that by Le et al. (2011, https://doi.org/10.1029/2010ja015781), who classified the TEC time series into anomalous and non‐anomalous days based on the TEC perturbation. They found that the anomalous day rate increased as the nucleation time of the earthquakes was approached, especially for larger and shallower earthquakes. We conduct the same analysis using random synthetic earthquakes. The anomalous day rate that is comparable to their result occurs in ∼40% of the 1,000 random trials, thereby suggesting that their result may also be an artifact.

Revisiting the Ionospheric Disturbances Over Low Latitude Region of China During Super Typhoon Hato

“…Comparatively, the ionospheric response to such events is generally weaker. In the meantime, owing to potential interruptions from above and limitations of the disturbance derivation method, clearly distinguishing the ionospheric responses to the ground geophysical events in certain conditions is still an open question (Eisenbeis & Occhipinti, 2021; Ikuta & Oba, 2022). The connection between severe meteorological events and ionospheric disturbances can be dated back to Bauer (1958), which showed the critical frequency of the F2 layer (foF2) increased as the hurricane approached, reaching its peak when the hurricane arrived at the ionosonde station.…”